Existing methods of developing and testing vehicles, including air, water, and land-based vehicles, typically involve both computer simulations and prototype testing. Unfortunately, computer simulations may be relatively time-consuming to perform and may undesirably simplify many of the complexities of the actual system. Similarly, prototype testing may be undesirably expensive. In the case of flight vehicles, conventional systems such as the BAT Unmanned Aerial Vehicle available from MLB Company of Mountain View, Calif., may only yield a relatively limited number of flight hours and conditions due to operating costs, logistical issues, safety regulations, and other factors.
Although prior art methods of developing and testing vehicles have achieved desirable results, there is room for improvement. More specifically, methods and systems that enable development and testing of algorithms and configurations of vehicles to be performed rapidly, accurately, and economically would have significant utility.